This document discusses knowledge graphs and how they can be used to drive intelligence into data. It describes how knowledge graphs can organize different types of data relationships and enable applications such as semantic search, pattern matching, and analyzing dependencies. Specific use cases are provided for skills discovery, root cause analysis, and military equipment management. Knowledge graphs are presented as a way to bridge data silos and enable a unified data fabric.

1. © 2022 Neo4j, Inc. All rights reserved.
© 2022 Neo4j, Inc. All rights reserved.
A Universe of
Knowledge Graphs
Dr. Maya Natarajan
Sr. Director, Product Marketing
maya.natarajan@neo4j.com
Dr. Jesús Barrasa
Sr Director, Sales Engineering
jesus.barrasa@neo4j.com

2. © 2022 Neo4j, Inc. All rights reserved.
© 2022 Neo4j, Inc. All rights reserved.
2
A knowledge graph is an
interconnected dataset
enriched with meaning so we
can reason about the
underlying data and use it
confidently for complex
decision-making.

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3
Driving Intelligence into Data with Knowledge Graphs
Data Graph
Dynamic Context
Knowledge Graph
Deep Dynamic Context
Organizing
Principle
Relationships

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Data Comes in Many Shapes & Sizes
A B C D E
A B C D E
One-to-Many
Relationships
Across Many
Entities
Small, Wide Data Complex Data Hierarchical & Recursive Data
Many-to-Many
Relationships
Nested Tree
Structures
Recursion (Self-
Joins)
Deep
Hierarchies
Link Inference
(If C relates to A and A relates to E,
then C must relate to E)
Node Similarity
Hidden Data
Legacy Data Frozen Data
Legacy SQL Systems Data Lake Fact Tables Graph Data Science - Machine Reasoning
A
C
E

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5
Driving Intelligence into Data with Knowledge Graphs
Data Graph
Dynamic Context
Relationships

6. © 2022 Neo4j, Inc. All rights reserved.
6
Driving Intelligence into Data with Knowledge Graphs
Data Graph
Dynamic Context
Knowledge Graph
Deep Dynamic Context
Organizing
Principle
Relationships

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7
What is Semantics?
Entity Resolution
& Analysis
Classification
& Tagging
Artificial
Intelligence
C O M P L E X I T Y
Synonym Rings Taxonomy Thesaurus Ontology
Controlled Vocabularies

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8
Driving Intelligence into Data with Knowledge Graphs
Data Graph
Dynamic Context
Knowledge Graph
Deep Dynamic Context
Organizing
Principle
Relationships

9. © 2022 Neo4j, Inc. All rights reserved.
Knowledge Graphs: The Foundation for Many Use Cases
ACTIONING
DATA ANALYTICS
DATA MANAGEMENT
DECISIONING
Aggregate Validate Govern Explore Deduce Infer Forecast Predict Prescribe
Graph Queries Graph Algorithms Graph Based ML
INTEGRATION
&
ENTITY
RESOLUTION
Semantic Search
Pattern Matching
Dependency

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Knowledge Graphs Bridge Data Silos…
Cross-Silo Connections

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… & Enable a Data Fabric
Cross-Silo Connections
Metadata
Validation
Semantics
Characteristics
Annotations
Disambiguation
Schema
DataOps
Discovery
Quality
Integration
Data Prep
Lineage
Governance
Reliability
Sharing
Operations &
Analytics
Contextual
Capabilities
Contextual
Intelligence
Heterogeneous
Data
SaaS or . . .
Business
Intelligence
Artificial
Intelligence
Analytics
Marketing Ops
Sales Ops
HR Analytics
Data-Driven
Apps

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Knowledge Graph for Metadata Management
(Dataportal) https://medium.com/airbnb-engineering/democratizing-data-at-airbnb-852d76c51770
(Amundsen) https://neo4j.com/blog/live-from-lyft/
(DataHub) https://engineering.linkedin.com/blog/2020/open-sourcing-datahub--linkedins-metadata-search-and-discovery-p
2017
2019
2019
2020

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15
The Semantic Search Knowledge Graph
A B C D E

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Semantic Search
Unstructured
Documents
Extracted
Entities
Taxonomy/
Ontology
NLP
Entity
Disambiguation

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17
Semantic Search
Challenge
Finding incidents that may have taken
place during missions to prevent future
disasters
Solution
Knowledge graph to comb through
millions of documents, reports, project
data, lessons learned, scientific
research, medical analysis, geospatial
data, IT logs, etc. stored nationwide.
Why Neo4j
Flexible, Contextual Data Model
$1M
Taxpayer funds
saved
2 yrs
Work saved
Quicker
Resolution of
issues

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18
The Pattern Matching Knowledge Graph

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Role
:HAS_SKILL
Python
Data
Integration
Project
Engineering
Java
Employee Neo4j
NodeJS
:REQ_SKILL
:HAS_SKILL :REQ_SKILL
:HAS_SKILL :REQ_SKILL
:IN
_D
EPT
:
R
E
Q
_
S
K
I
L
L
:FOR_PROJECT
:HAS_SKILL
:CANDIDATE_FOR
{score: 0.75}
Knowledge Graphs allow you to
make implicit
relationships….
….explicit
Moving from Implicit to Explicit

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Neo4j, Inc. All rights reserved 2021
20
Pattern Matching = Hidden Value
6,100 employees
1 million calls
500,000 claims
Identify
Unknown Transformative Patterns
Uncover New Answers

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21
What are Industries & Use Cases
Recommendation/
Personalization
Customer Journey
Fraud Detection
Single View
Skills Discovery
Patient Journey
Literature Discovery
Retail Financial
Small and Wide Data Hidden Data
One-to-Many
Relationships Across
Many Entities
Many-to-Many
Relationships
Life Sciences & Healthcare
Link Inference
(If C relates to A and A relates to E,
then C must relate to E)
Node Similarity

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23
Skills Discovery
Challenge
A loss of skilled, trained employees
due to workforce reduction
Solution
Knowledge graph combined with
AI/ML across their various siloed
employee skills, learning and
workforce planning and resource
management databases
Why Neo4j
Flexible, Contextual Data Model
Quicker
Identification &
filling of skills gaps
Automated
Personalized
recommendations

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24
The Dependency Type Knowledge Graph
A
D
B C

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25
Dependencies, Dependencies… Oh My!

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Dependencies, Dependencies… Oh My!
A
B
C
H
I
D
J
N
F
E
G
L
M
Depends on
Dep
end
s
on
De
pen
ds
on
Dep
end
s
on
De
pe
nd
s
on
De
pe
nd
s
on
D
e
p
e
n
d
s
o
n
Depends on
Depends
on
D
e
p
e
n
d
s
o
n
D
e
p
e
n
d
s
o
n
Depends on
D
e
p
e
n
d
s
o
n

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Neo4j, Inc. All rights reserved 2021
27
Small Dependency = Big Impact
Single Component Manufacturer
Shuts Down
Entire Supply Chain Affected
30,000 components
4,000 suppliers
1,800 parts
19 hours assembly time / car
1,450 cars / day

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28
What are Industries & Use Cases
Data Lineage
Track & Trace
Root Cause Analysis
Impact Analysis
What-If Analysis
Redundancy
Bottlenecks
Supply Chain Telecomm
Small and Wide Data Hierarchical and Recursive
One-to-Many
Relationships Across
Many Entities
Nested
Tree
Structures
Recursion
(Self-Joins)
Deep
Hierarchies
Many-to-Many
Relationships
Manufacturing

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29
Diving Into An Example
:DEPENDS_ON
:DEPENDS_ON
:DEPENDS_ON
IF/AX2431
💥
Customer
Event Correlation
Root Cause Analysis
Event Prioritization
Impact Analysis

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5B
Nodes
14B
Relationships
7.5x
Faster
77%
Lower DB admin
“
30
Force Readiness
Neo4j enables analysts to save huge amounts of
time. Answers are immediate. As a result, the
parts delivery is more accurate and order
turnaround is much faster.
Preston Hendrickson
US Army Project, CALIBRE
Challenge
Slow, inflexible & expensive
PLM system for military equipment
Bill of Materials Management
Solution
Knowledge graph of components & costs
to determine lifespan of equipment for
ordering, budgeting and what-if analyses
Why Neo4j
Flexible, Contextual Data Model

28. © 2022 Neo4j, Inc. All rights reserved.
© 2022 Neo4j, Inc. All rights reserved.
31
A Universe of Knowledge Graphs
Questions?
Contact us at
maya.natarajan@neo4j.com
jesús.barrasa@neo4j.com